Modelling-based evaluation of the effect of quarantine control by the Chinese government in the coronavirus disease 2019 outbreak
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SciScore for 10.1101/2020.03.03.20030445: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources We adopted the following ordinary differential equation (ODE) model to simulate the epidemic of COVID-19 for each investigated population: where S, E, I, and R were the number of susceptible, latent (or exposed), infectious, and removed individuals (including recovered individuals and death) at time t and N − S + E + I + R is the size of population.
N − S + E + Isuggested: NoneSoftware and Algorithms Sentences Resources We used R packages such as ggplot2 and plotly for graphics. ggplot2suggested: (ggplot2, RRID:SCR_014601)Results from OddPub: We did not detect open data. We …
SciScore for 10.1101/2020.03.03.20030445: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources We adopted the following ordinary differential equation (ODE) model to simulate the epidemic of COVID-19 for each investigated population: where S, E, I, and R were the number of susceptible, latent (or exposed), infectious, and removed individuals (including recovered individuals and death) at time t and N − S + E + I + R is the size of population.
N − S + E + Isuggested: NoneSoftware and Algorithms Sentences Resources We used R packages such as ggplot2 and plotly for graphics. ggplot2suggested: (ggplot2, RRID:SCR_014601)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Nonetheless, our study has several major limitations. Firstly, we were not able to derive a generalized model with finalized parameters to fit the overall epidemic spreading. Instead, the model parameters were estimated in a dynamic manner in our study. This is in line with the observation of dynamic transmission properties of the virus15. Secondly, the significance of the model largely depends on the accuracy of estimated parameters. Although there is not a golden standard so far to evaluate the accuracy of our model parameters, the estimated duration of incubation (1/σ) from our model-derived parameter incubation rate (σ) is highly in agreement with previous estimations by other studies7–10, and the dynamic values of the infectious rate (β) is within the range of the recent estimation by Yang et al.14. These observations suggest our approach for model parameter estimation is plausible. Thirdly, our epidemic forecast was somehow sensitive to our prediction of parameters which were estimated from their overall dynamic patterns. Nonetheless, such forecasting would still be accurate in a short period. In this regard, artificial intelligence (AI)-inspired methods14,16 may be alternatives to epidemiological models for the real-time forecasting of transmission dynamics of COVID-19. The fact that the severity and the fatality rate remain unchanged during the whole epidemic course suggests that the biology of the virus itself did not change over time; this is in line with genetic se...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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